Propensity Score Matching {https://t.co/j62sAAqC5M} #rstats #DataScience
— R-bloggers (@Rbloggers) April 12, 2022
Upcoming R conferences (2022) {https://t.co/cE6ojR6jVZ} #rstats #DataScience
— R-bloggers (@Rbloggers) April 8, 2022
R-spatial evolution: retirement of rgdal, rgeos and maptools {https://t.co/E3zBXZ95fq} #rstats #DataScience
— R-bloggers (@Rbloggers) April 13, 2022
Bayesian Estimation by using rjags Package {https://t.co/7eS2LoQizF} #rstats #DataScience
— R-bloggers (@Rbloggers) April 9, 2022
Number of PhDs by Field {https://t.co/xsg8Y8Mxd8} #rstats #DataScience
— R-bloggers (@Rbloggers) April 11, 2022
A *simple* introduction to ggplot2 (for plotting your data!) {https://t.co/0ixGpE509b} #rstats #DataScience
— R-bloggers (@Rbloggers) April 14, 2022
Bayesian Estimation of Nelson-Siegel model using rjags R package {https://t.co/Ez6nQ3uirV} #rstats #DataScience
— R-bloggers (@Rbloggers) April 12, 2022
Selection bias and observed values {https://t.co/xdRQGMK95g} #rstats #DataScience
— R-bloggers (@Rbloggers) April 14, 2022
How to collect dataviz from Twitter into your note-taking system {https://t.co/JW24TvhhFB} #rstats #DataScience
— R-bloggers (@Rbloggers) April 14, 2022
The sftime Package {https://t.co/NnLycZsJnl} #rstats #DataScience
— R-bloggers (@Rbloggers) April 12, 2022
Pulling Twitter Engagements Using the v2 API as Well as rtweet {https://t.co/O2GCijRiuM} #rstats #DataScience
— R-bloggers (@Rbloggers) April 12, 2022
Predicting Twenty 20 Cricket Result with Tidy Models {https://t.co/SY82ltIOnp} #rstats #DataScience
— R-bloggers (@Rbloggers) April 13, 2022
Sentiment Analysis of Tweets {https://t.co/oUo7oEPJOc} #rstats #DataScience
— R-bloggers (@Rbloggers) April 4, 2022
Classification: Logistic Regression and Random Forest {https://t.co/i18v8RedYE} #rstats #DataScience
— R-bloggers (@Rbloggers) March 31, 2022
R Shiny in Life Sciences – Top 7 Dashboard Examples {https://t.co/iNZgHjyP7K} #rstats #DataScience
— R-bloggers (@Rbloggers) March 29, 2022
How to Use R and Python Together? Try These 2 Packages {https://t.co/bBnt7pG52N} #rstats #DataScience
— R-bloggers (@Rbloggers) March 22, 2022
Basics of Text Mining in R {https://t.co/14MYZXbGiB} #rstats #DataScience
— R-bloggers (@Rbloggers) April 1, 2022
Propensity Score Matching {https://t.co/j62sAAqC5M} #rstats #DataScience
— R-bloggers (@Rbloggers) April 12, 2022
Enjoying the process of making tables in R using {reactable} and {reactablefmtr} {https://t.co/Ds2wKP1BqZ} #rstats #DataScience
— R-bloggers (@Rbloggers) April 7, 2022
R Shiny in Government – Top 7 Dashboards You Should See {https://t.co/K9B5t5rUyM} #rstats #DataScience
— R-bloggers (@Rbloggers) April 5, 2022
Kruskal-Wallis test, or the nonparametric version of the ANOVA {https://t.co/J0W0co9lrX} #rstats #DataScience
— R-bloggers (@Rbloggers) March 24, 2022
Dual axis charts in ggplot2 – how to make them and why they can be useful {https://t.co/EorkOeHu04} #rstats #DataScience
— R-bloggers (@Rbloggers) April 7, 2022
Visualizing economic data with pretty worldmaps {https://t.co/A3CfPt4p3u} #rstats #DataScience
— R-bloggers (@Rbloggers) March 24, 2022
How I analyze 100+ ggplots at once {https://t.co/L6oo0NwRq1} #rstats #DataScience
— R-bloggers (@Rbloggers) March 30, 2022
---
title: "RBloggers Top Tweets"
output:
flexdashboard::flex_dashboard:
vertical_layout: scroll
source_code: embed
theme:
version: 4
bootswatch: yeti
css: styles/main.css
---
```{r setup, include=FALSE}
library(flexdashboard)
library(dplyr)
library(httr)
library(lubridate)
library(jsonlite)
library(purrr)
rbloggers <- fromJSON("data/rbloggers.json")
get_tweet_embed <- function(user, status_id) {
url <-
stringr::str_glue(
"https://publish.twitter.com/oembed?url=https://twitter.com/{user}/status/{status_id}&partner=&hide_thread=false"
)
response <- GET(url) %>%
content()
return(shiny::HTML(response$html))
}
```
Column {.tabset .tabset-fade}
-----------------------------------------------------------------------
### Top Tweets - 7 days {.tweet-wall}
```{r}
rblog_7 <- rbloggers %>%
mutate(created_at = as_date(created_at)) %>%
filter(created_at %within% interval(start = today() - 7, end = today())) %>%
slice_max(favorite_count + retweet_count, n = 12)
rblog_7_html <-
map2_chr(rblog_7$screen_name, rblog_7$status_id, get_tweet_embed)
shiny::HTML(stringr::str_glue("{rblog_7_html}"))
```
### Top Tweets - 30 days {.tweet-wall}
```{r}
rblog_30 <- rbloggers %>%
mutate(created_at = as_date(created_at)) %>%
filter(created_at %within% interval(start = today() - 30, end = today())) %>%
slice_max(favorite_count + retweet_count, n = 12)
rblog_30_html <-
map2_chr(rblog_30$screen_name, rblog_30$status_id, get_tweet_embed)
shiny::HTML(stringr::str_glue("{rblog_30_html}"))
```